Runtime vs OpenAI Dots

OpenAI Dots and Runtime at a glance

OpenAI Dots are always-on personal agents in ChatGPT, launched at DevDay on September 29, 2026. Each Dot runs on GPT-6 Astra and has its own computer and browser in the cloud, so it keeps working when your laptop is off. It can research, analyze data, prepare documents, and build software, using the plugins you connect (OpenAI's plugin ecosystem covers more than 4,000 apps). You reach it in ChatGPT on desktop, web, and mobile, by voice, in Slack, or in Microsoft Teams. It remembers your preferences from your conversations, ChatGPT memory, and its own notes. Dots are for an individual who wants a capable assistant that keeps going between conversations.

Runtime is the AI agent harness for payment and fintech teams: an operating system for building and running many agents across the org, not one agent per person. Anyone on payment ops, risk, compliance, finance, underwriting, onboarding, or support builds agents from their SOPs. Agents work on isolated computers in your cloud, reach your ledger, processor, and bank portals through APIs, databases, CLIs, MCP servers, and a browser, and stop for a person before anything moves money.

Good products, different jobs. Dots make one person more productive. Runtime runs the money operations of a whole team.

How they differ

One vendor's stack vs no single-vendor dependency

Dots run on OpenAI's model, on OpenAI's cloud computer, inside ChatGPT. That is a tightly integrated product, and it means your agent's availability, pricing, and model roadmap follow one vendor.

Runtime is multi-cloud, multi-sandbox, and multi-model. Agent computers run in your AWS, GCP, or Azure account, or fully self-hosted via Helm. You bring your own sandbox provider, with fallbacks. You choose the models: Anthropic, OpenAI, Google, or open-weight models served in your cloud for PCI and PII work, with harness routing across Claude Code, Codex, and OpenCode. If one provider has an outage, changes pricing, or deprecates a model, your agents keep running.

Guardrails a person sets vs guardrails the org sets

Dots start with built-in safeguards and an automatic review before actions that affect accounts or share information. Each user can add custom rules: take action without asking, take action when told, ask first, or hand off. A safety monitor can pause or stop a Dot. In Enterprise, Dots are off until an admin enables them and sets who can use them. These controls are designed around one person's accounts.

Runtime guardrails are set for the organization and the money. Agents start read-only. Releasing a payout, applying a reserve, booking a ledger entry, or replying to a sponsor bank waits for an approver in Slack or Teams. Credentials are masked, card numbers and SSNs are stripped from prompts and logs, and RBAC decides who can build, run, and approve. Every run is recorded end to end: trigger, every query and tool call, approvals, cost, and result. The record your sponsor bank or examiner asks for stays with you.

A personal agent vs agents built for teams

Dots are personal. At launch each eligible user gets one Dot, and its memory is that user's preferences and work.

Runtime is built for teams: shared agents, templates, and memory across support, payment ops, finance, risk, and compliance, with real-time collaboration, spend controls, and role-based access. A single stuck payment touches four teams. Support gets the ticket, payment ops traces it, finance sees a reconciliation break, and risk or compliance may review it. With personal agents, each person investigates separately. On Runtime it is one investigation with one record, and every run adds to the organization's memory of resolved tickets, fraud caught, and reconciliation edge cases.

Built for payments, with an engineer

Dots are self-serve in ChatGPT and horizontal: research, documents, software, launch materials.

Runtime pairs you with a forward-deployed AI engineer from a team that built payment and fintech infrastructure at Hulu's payments team at Disney, Finix, Modern Treasury, and BlackRock's AI quant group. The FDE maps your processes, builds the first agents with your team, sets up guardrails, and trains admins. When a process is solved, agents can turn it into a deterministic script in your repos, so engineers own it if it becomes mission-critical. Rain replaced $250k in vendor spend with Runtime.

Where Dots is stronger

• Zero setup for an individual. It lives inside ChatGPT, which many people already use daily.
• Breadth of apps. More than 4,000 apps through OpenAI's plugins, plus a connection to your own computer.
• Always on, everywhere you are. ChatGPT, voice, Slack, and Teams, with one memory across them.
• Personal knowledge work. Research, data analysis, documents, and software, carried across many conversations.
• Included in the plan. One Dot comes with Pro or Business Premium at no extra cost.

Pricing

Dots: one Dot is included with ChatGPT Pro and Business Premium at no extra cost, and Enterprise workspaces can try the beta. OpenAI says additional Dots and more speed or monthly capacity will be available later; those prices are not published.

Runtime has public tiers: Free ($0, one session), Teams from $99 per seat per month, and Enterprise with custom pricing and self-hosting. The value to weigh it against is the work of the analysts you were about to hire.

Which should you choose

Choose Dots if

• You want a personal agent for research, writing, and analysis
• Your team already works in ChatGPT and the work is individual
• OpenAI's model and cloud meet your data requirements
• No agent action moves money or touches card and SSN data

Choose Runtime if

• Payment ops, risk, compliance, or finance need shared agents on real queues
• You cannot depend on one cloud, sandbox, or model provider
• Approvals before money moves and an examiner-ready record are requirements
• You want a forward-deployed engineer who knows payments

Many teams will run both: Dots for personal productivity, Runtime for the operations work around every transaction.

Frequently asked questions

What is OpenAI Dots?

Dots are always-on agents in ChatGPT, announced at OpenAI DevDay on September 29, 2026. Each Dot runs on GPT-6 Astra with its own cloud computer and browser, keeps working toward a goal between conversations, uses the apps you connect, and messages you in ChatGPT, Slack, or Microsoft Teams when it needs a decision.

Who can use OpenAI Dots?

Dots are rolling out to ChatGPT Pro and Business Premium users, with a beta for Enterprise workspaces that admins must turn on. One Dot is included with a Pro or Business Premium plan. OpenAI says more Dots and more capacity per Dot will come later, at prices it has not published.

Can OpenAI Dots be used for payment operations?

A Dot can work across connected apps and ask before sensitive actions, which helps an individual. Payment operations usually also need agents in your own cloud, approvals tied to money movement, PCI and PII data stripped from prompts, and a record per run your sponsor bank can review. Runtime is built for that.

Does Runtime work with OpenAI models?

Yes. Runtime is multi-model: Anthropic, OpenAI, Google, and open-weight models, with harness routing across Claude Code, Codex, and OpenCode. If one provider has an outage or deprecates a model, agents fall back to another.

Can we use Dots and Runtime together?

Yes. Individuals can keep a Dot for personal research and drafting, while payment ops, risk, finance, and compliance run shared, governed agents on Runtime.